Application of Remote Sensing and GIS in Mineral Alteration Mapping and Lineament Extraction Case of Oudiane Elkharoub (Requibat Shield, Northern of Mauritania)

The integration of remotely sensed data allowed the successful characterization of the mineral alteration zones of the Oudiane Elkharoub area in the Northeastern part of Reguibat Shield using image transformation techniques. As both chemical and geochemical analyses showed significant Au, Ag, Cu, Pb, Mn, Cr, Ni, Th and Y anomalies, it’s very interesting to apply the remote sensing and GIS in mineral resources mapping. The remote sensing is a direct adjunct to the field, lithologic and structural mapping, and more recently, GIS has played an important role in the study of mineralization areas. The integration of several evidential maps highlighted the plausible areas with high concentrations of chlorite, epidote, kaolinite, calcite, alunite, hematite, illite and sulfur among other key mineral alterations that reflect the intensity of hydrothermal effects and the probable sites of ore bodies. The methodological approach integrates geological information acquired from Aster and Landsat 8 OLI/TIRS (Operational Land Imager/Thermal InfraRed Sensor) images and a multi-criteria GIS analysis. The superimposition of various lineament and hydrothermal alteration maps and the consideration of precious and base metal indicators allowed the zoning of sites likely to contain mineral concentrations. Remote sensing becomes an important tool for locating mineral deposits in its own right, when the primary and secondary processes of mineralization result in the formation of spectral anomalies. Reconnaissance lithological mapping is usually the first step of mineral resource mapping. This is complimented with structural mapping, as mineral deposits usually occur along or adjacent to geologic structures, and alteration mapping, as mineral deposits are commonly associated with hydrothermal alteration of the surrounding rocks. Ground truthing and laboratory studies including XRD analysis were utilized to verify the results.

Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

Pegmatite remote sensing extraction and metallogenic prediction in Azubai area,Xinjiang

Remote sensing technique plays an important role in geological prospecting in Altay because of the remote location and steep terrain with mountains. Pegmatite has important implications for metallogenic prospecting as most of rare metals occurs in it. Pegmatite information from optical and radar images was extracted, and the spatial distribution and scale of pegmatite were generalized in Azubai, Altay. Three mining targets, that is, Halon-Azubai, Kuermutu-Tuyibaguo and Zhuolute-Akuoyige, were delineated based on the analysis of pegmatite information, structure interpretation and other geological data.

Remote Sensing Technology for Identification of Alteration Information of Gold Deposits in the Eastern Tianshan Area, Xinjiang

Based on specific well-exposed rocks useful for high-quality remote sensing interpretation in the gold-prospecting area in the eastern Tianshan, this paper gives a detailed description of a remote sensing model for metallogenic prediction. The model reveals that multi-spectral remote sensing data are integrated with high-resolution remote sensing data, and enhanced extraction and visual description of weak remote sensing information are used for prospecting. This model has tested in the given gold deposit, and used successfully in Au-Cu prospecting in the Kalatage area.

Some essential questions in remote sensing science and technology

In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation? Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.

Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review

热带气旋(TC)严重危害人类生命和财产安全,TC的实时监测一直是研究热点,随着空间和传感器技术的发展,卫星遥感已成为监测TC的主要手段.此外,深度学习具有卓越的数据挖掘能力,在地球科学中的表现优于基于物理或统计的算法,越来越多的深度学习算法被开发和应用于TC信息的提取,本文系统地回顾了深度学习在TC信息提取中的应用,并给出了深度学习模型在TC强度和风圈半径提取中的应用.此外,本文还展望了深度学习在TC信息提取中的应用前景.

Remote Sensing Estimation of Crop Lead Pollution Stress Degree Using Wavelet Analysis

Accurate estimation of soil lead pollution degree is one of the key steps in controlling soil lead pollution; vegetable hyperspectral features research provided a new approach to discovering and monitoring soil heavy metal pollution.Spectral reflectance implies information of pollution impacts on vegetation;estimation of lead pollution degree based on the spectral reflectance is equivalent to extraction of weak information.This study puts forward a new feature extraction method based

基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法

利用遥感技术快速准确地提取耕地信息是耕地保护的关键环节。以山东省商河县为例,提出了一种基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法。首先采用毯子覆盖法计算多季相遥感影像每个像元的上分形信号和下分形信号,对比分析耕地和其他土地利用类型的分形特征,选取上分形信号的第3尺度作为特征尺度,提取商河县耕地空间分布特征;其次采用同时期的土地利用矢量数据、Esri land cover数据和统计数据进行耕地信息提取精度评价;最后分别设置多季相分形提取与单季相分形提取、现有土地利用数据产品的对比实验,并基于点位匹配度和面积匹配度进行评价。结果表明:多季相数据更能反映农作物生长的复杂性,有助于提高耕地信息的提取精度;不同土地利用类型在不同分形尺度的信号值各不相同,分形特征可以在不同尺度上清晰地刻画出不同土地利用类型的分异性;基于矢量数据和Esri land cover数据评价的多季相分形特征耕地提取点位匹配度为87.13%和89.83%,面积匹配度为99.73%和97.91%,均比单季相分形提取结果精度高;综合考虑点位匹配度、面积匹配度和空间分布特征,研发方法能有效区分耕地和其他土地利用类型,提取结果更优,且与统计数据有更高的一致性。该方法可准确提取耕地信息,为耕地的动态监测和损害评估提供技术支撑。

Integrating Aster Images Processing and Fieldwork for Identification of Hydrothermal Alteration Zones at the Oumjrane-Boukerzia District, Moroccan Anti-Atlas

Mapping from remote sensing has become more effective in the field of geology, mainly in lithological discrimination and identification of hydrothermal alteration zones. The use of this technique consists in obtaining information about the rock mass and the main ones existing in the inaccessible areas. Satellite data from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor represent a favorable potential for detecting the spectral signatures of mineral zones and identifying their nature. These data are more reliable in places where the climate is arid with less abundant vegetation, as at the Oumjrane-Boukerzia mining district. This region which is part of the Eastern Anti-Atlas, is composed of several mineralized veins which still require detailed studies and exploration by the technique of remote sensing. In this work we applied several processing techniques on ASTER imagery such as Colored Composition, Principal Component Analysis and Ratio Bands. The use of the reports of the specialized Bands makes it possible to identify some hydrothermal alteration minerals within the mining district of Oumjrane Boukerzia. These minerals are represented mainly by iron oxides and hydroxides (Hematite, jarosite, limonite and goethite), carbonate minerals (dolomite, calcite), clay minerals (Illite, kaolinite and chlorite) and quartz minerals. This work allows us to produce a map of hydrothermal alteration zones which can be used as a valuable reference in the strategy of mining exploration for the base metals (Cu, Pb, Zn and Ba), in the mining district of Oumjrane-Boukerzia and in the entire Eastern Anti-Atlas.

Research on Extraction Method of Surface Information Based on Multi-Feature Combination Such as Fractal Texture

Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.

基于Landsat-8 OLI数据的新疆昭苏南克拉克斯赛依矿区蚀变信息提取

昭苏南克拉克斯赛依矿区气候条件恶劣,高寒缺氧,交通不便,积雪覆盖深厚,区内构造复杂,矿产资源丰富。充分发挥遥感技术的独特优势,对研究区未来的找矿工作有重要意义。文章将Landsat-8 OLI作为数据源,在预处理基础上,根据研究区矿产地质情况及围岩蚀变特征,采用主成分分析法进行铁染、羟基蚀变信息提取,结果表明:研究区蚀变异常信息分布特征具有一定规律,异常信息呈带状展布,与构造走向基本一致,羟基异常与铁染异常套合较好,且强度较高,结果与研究区内已知矿化点套合较好,证明蚀变信息为良好的找矿标志,对研究区找矿工作有重要的指导意义。

Fast Remote-Sensing Image Registration Using Priori Information and Robust Feature Extraction

In this paper, we propose a fast registration scheme for remote-sensing images for use as a fundamental technique in large-scale online remote-sensing data processing tasks. First, we introduce priori-information images,and use machine learning techniques to identify robust remote-sensing image features from state-of-the-art ScaleInvariant Feature Transform（SIFT） features. Next, we apply a hierarchical coarse-to-fine feature matching and image registration scheme on the basis of additional priori information, including a robust feature location map and platform imaging parameters. Numerical simulation results show that the proposed scheme increases position repetitiveness by 34%, and can speed up the overall image registration procedure by a factor of 7：47 while maintaining the accuracy of the image registration performance.

基于Landsat TM的个旧锡矿成矿信息提取与找矿预测

在对云南个旧锡矿矿区成矿地质环境、地质特征和成矿规律研究的基础上,以Landsat TM多光谱影像数据为基础信息源,利用遥感找矿技术对个旧锡矿地质构造信息和蚀变异常信息进行提取。在此基础上,综合利用已有的地质、物探和化探成果,结合野外实地调查后圈定了3类共9个找矿远景区。

基于决策树的Landsat TM/ETM+图像中太湖蓝藻水华信息提取

以9期Landsat TM/ETM＋影像为数据源,基于K-T变换和归一化植被指数（NDW）,建立了湖泊蓝藻水华信息提取的决策树模型.基于大气顶面反射率图像,选用2005年10月17日太湖图像进行了对比验证,表明决策树模型比单波段阈值法、多波段阈值法（RVI、DVI、NDW）能够更有效地提取蓝藻水华信息,区分陆生植被、水生植物和水华,省去了水体掩膜的过程.使用太湖2002年10月25日和2011年7月22日图像、巢湖2005年8月12日的图像,验证决策树模型方法和工作流程的有效性.使用多期TM图像确定了阈值的取值范围,其中,亮度、绿度、NDVI的下限值依次为0.191、-0.007、-0.054,湿度下限范围为0.07～0.15;亮度阈值上限范围为0.3～0.7、绿度为0.2～0.5、湿度为0.1～0.3,这些结果可作为湖泊蓝藻水华遥感监测的参考.

基于Landsat TM的热带精细地物信息提取的模型与方法——以海南岛为例

应用遥感技术进行精细地物信息提取是研究生态系统结构、过程和功能的重要手段之一。由于热带地区生态系统复杂,为精细地物信息提取带来很大的不确定性,极易产生"同物异谱"、"同谱异物"的现象。研究以地处热带地区的海南岛精细地物遥感信息提取为例,在综合分析典型地物光谱特征、空间分布、斑块形状等基础上,构建和优化了水陆指数WLI(Water andLand differing Index)、乔灌草指数GSI(Grass and Shrub differing Index)、旱地-沙地指数SSI(Field and Sand differing Index),并结合新型通用植被指数VIUPD(Vegetation Index of the Universal Pattern Decomposition Method)及DEM(Digital Elevation Model)等多源数据,提出基于决策树的面向对象遥感信息提取方法。该方法首先确定要提取的对象,明确对象类别与对象隶属关系,然后逐层逐项的提取天然林、橡胶林、浆纸林等地物信息。结果表明,综合提取的精度达88%,相比传统的监督分类方法精度(66%)提高22个百分点,精度明显提高。

基于Landsat-TM影像的鄱阳湖典型湿地动态变化研究

利用分层分类法,通过对鄱阳湖典型湿地（蚌湖与赣江中支口三角洲）长序列秋季Landsat-TM影像进行解译分析,探讨了1991年-2008年间鄱阳湖典型湿地动态变化特征。结果表明分层分类方法能够有效地应用于Landsat-TM遥感影像的解译;从1991年到2008年蚌湖和赣江中支口三角洲湿地的植被面积分别增加18.56km2和6.01km2,其中赣江主支三角洲洲滩植被分布呈向湖体扩展态势。植被分布受水情影响比较大,蚌湖湿地的苔草面积与同时期水面积呈负相关性,而赣江主支三角洲湿地植被类型结构变化受水位影响也比较明显,苔草面积变化与秋季湖口水位表现为负相关,芦苇分布面积变化则与湖口水位变化趋势较为一致。

多时相Landsat影像的平原河网区不透水面信息提取方法与应用

不透水面是衡量城市生态环境的重要指标,针对平原河网区不透水面与水体、裸土等地物较难区分的问题,以苏北里下河平原快速城镇化区为研究对象,利用多时相Landsat影像为数据源,基于像元光谱特征及其季节性变化分析,构建了基于时序NDWI、NDVI和NDBI的决策树模型,并利用GIS空间分析技术对不透水面的时空变化特征进行了分析。结果表明:多时相光谱信息可有效改善水体、裸土和稀疏植被等像元与不透水面的混分,2005年和2016年的不透水面分类总体精度和Kappa系数均在0.85以上,合理反映了不透水面以向东和向南扩张为主的趋势特征,年均扩张速度约为6.7 km2。研究成果为该区城镇化下的生态环境效应研究提供数据基础,同时可为其他平原河网区不透水面信息提供借鉴和参考。

高寒湿地遥感信息提取方法综述

高寒湿地位于高纬度、高海拔的寒冷地区,具有独特的气候和生态环境特征,为人类社会提供了重要的生态系统服务,对维持区域和全球生态平衡至关重要。高寒湿地遥感信息提取可以明确高寒湿地的边界和空间分布,对探索高寒湿地时空演变规律及驱动力分析具有重要意义。在梳理相关文献的基础上阐述了基于遥感的高寒湿地类型识别和湿地生态系统参数反演方法,概述了各方法的技术手段、优缺点及其适用性,从多源数据融合、算法融合及面向实际需求的角度展望了高寒湿地遥感信息提取方法的研究。

基于Landsat7 ETM+图像提取蛤蟆沟林场浅覆盖区蚀变遥感异常

受植被、地形、阴影、第四系等干扰因素影响,覆盖区的遥感蚀变异常提取是一项具有探索性的研究课题。以内蒙古自治区阿尔山市蛤蟆沟林场为研究区,根据蚀变岩光谱特征,利用Landsat7 ETM+多光谱图像,在剔除多种干扰因素的基础上,运用主成分分析法提取了浅覆盖区蚀变遥感异常,分析了蚀变分布特征与影响因素,指出下一步应加强植被抑制和消除地形阴影效应研究。

Landsat8 OLI数据斑岩铜矿遥感蚀变矿物组合提取研究

Landsat8 OLI数据NIR波段(0. 845~0. 885μm)和SWIR2波段(2. 100~2. 300μm)波谱分辨率的提高,已分别成为含Fe^(3+)类、Al-OH类和Mg-OH类蚀变矿物的诊断性谱段。通过利用混合调制匹配滤波(mixture tuned matched filtering,MTMF)方法,开展多龙矿集区铁格隆远景区含Fe^(3+)类、Al-OH类和Mg-OH类蚀变矿物信息提取研究,并与Hyperion数据蚀变矿物信息提取结果进行对比分析。研究结果表明,基于Landsat8 OLI提取的3类蚀变矿物较为可靠;铁格隆远景区蚀变矿物组合的空间分布与斑岩铜矿经典蚀变分带特征基本吻合;遥感蚀变分带由内而外分别为绢英岩化+泥化带(Al-OH类蚀变矿物)和青磐岩化带(Mg-OH类蚀变矿物),Fe^(3+)矿物组合则分布在绢英岩化+泥化带和青磐岩化带之间或过渡带上。